research-article

Improving motif refinement using hybrid expectation maximization and random projection

Authors:

H. S. Shashidhara,

K. G. SrinivasaAuthors Info & Claims

ISB '10: Proceedings of the International Symposium on Biocomputing

Article No.: 20, Pages 1 - 7

https://doi.org/10.1145/1722024.1722048

Published: 15 February 2010 Publication History

Abstract

The main goal of the motif finding problem is to detect novel, over-represented unknown signals in a set of sequences. Popular algorithms like Expectation Maximization (EM) and Gibbs sampling are sensitive to the initial guesses and are known to converge to the nearest local maximum very quickly. A novel optimization framework searches the neighborhood regions of the initial alignments in a systematic manner to explore the multiple local optimal solutions. This effective search is achieved by transforming the original optimization problem into its corresponding dynamical system and estimating the practical stability boundary of the local maximum. The work aims at implementing the hybrid algorithm and enhancing it by trying different global methods and other techniques. Then aggregation methods rather than projection methods are tried.

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Cited By

Yahaya YAjadi JSanusi RSawlan ZAdegoke N(2025)Hybrid random projection technique for enhanced representation in high-dimensional dataExpert Systems with Applications10.1016/j.eswa.2024.125569262(125569)Online publication date: Mar-2025
https://doi.org/10.1016/j.eswa.2024.125569
Clemente JAdorna H(2013)Some Improvements of Parallel Random Projection for Finding Planted (l,d)-MotifsTheory and Practice of Computation10.1007/978-4-431-54436-4_5(64-81)Online publication date: 2013
https://doi.org/10.1007/978-4-431-54436-4_5
Clemente JCabarle FAdorna H(2012)PROJECTION Algorithm for Motif Finding on GPUsTheory and Practice of Computation10.1007/978-4-431-54106-6_9(101-115)Online publication date: 2012
https://doi.org/10.1007/978-4-431-54106-6_9

Index Terms

Improving motif refinement using hybrid expectation maximization and random projection
1. Applied computing
  1. Life and medical sciences

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cover image ACM Other conferences

ISB '10: Proceedings of the International Symposium on Biocomputing

February 2010

312 pages

ISBN:9781605587226

DOI:10.1145/1722024

Conference Chair:
Dan Tulpan
National Research Council of Canada- Institute of Information Technology
,
Program Chairs:
Mathew J. Palakal
Indiana University Purdue University Indianapolis, USA
,
K. A. Abdul Nazeer
National Institute of Technology Calicut, India
,
Aswati Nair R.
National Institute of Technology Calicut, India

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Indiana University Purdue University, Indianapolis
National Institute of Technology, Calicut, India

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SIGAPP: ACM Special Interest Group on Applied Computing

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 February 2010

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ISB '10: International Symposium on BioComputing

February 15 - 17, 2010

Kerala, Calicut, India

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Cited By

Yahaya YAjadi JSanusi RSawlan ZAdegoke N(2025)Hybrid random projection technique for enhanced representation in high-dimensional dataExpert Systems with Applications10.1016/j.eswa.2024.125569262(125569)Online publication date: Mar-2025
https://doi.org/10.1016/j.eswa.2024.125569
Clemente JAdorna H(2013)Some Improvements of Parallel Random Projection for Finding Planted (l,d)-MotifsTheory and Practice of Computation10.1007/978-4-431-54436-4_5(64-81)Online publication date: 2013
https://doi.org/10.1007/978-4-431-54436-4_5
Clemente JCabarle FAdorna H(2012)PROJECTION Algorithm for Motif Finding on GPUsTheory and Practice of Computation10.1007/978-4-431-54106-6_9(101-115)Online publication date: 2012
https://doi.org/10.1007/978-4-431-54106-6_9

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